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Abstract
Data1 is a dataframe with 7 variables: 1) id = female identity, 2) RS = annual reproductive success of females aged 7 years and over (0 = failed, 1 = success), 3) year, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) alo = age at last observation, 6) ROScurrent = rain-on-snow experienced in current year, 7) age. Data2 is a dataframe with 7 variables: 1) id = female identity, 2) RS = annual reproductive success of females aged 2-6 years (0 = failed, 1 = success), 3) year, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) alo = age at last observation between 2 and 6 years, 6) ROScurrent = rain-on-snow experienced in current year, 7) age . Data3 is a dataframe with 5 variables: 1) id = female identity, 2) year, 3) preg = annual pregnancy probability of females aged 2-6 years, 4) ROSutero = rain on-snow events experienced in utero (0 = high, 1 = low), 5) BM = body mass. All continuous variables have been centered and divided by two standard deviations.